 | Run 14750 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-5 |
| Dataset | MulticlassClassificationData |
| Task type | CollaborativeFiltering |
| Created | 1y309d ago |
| Download | Login required! |
Done! 
| 1s | |
| 418M | |
| CollaborativeFiltering | |
| 0.189 | |
| 0.152 | |
| 0.204 | |
| 0.164 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 0.13 ratings range: [0, 1] training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054 MatrixFactorization num_factors=5 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.4361830 memory 0 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [1s] ===== MAIN: predict/evaluate on train data ===== === START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in === END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [1s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 0.1 ratings range: [0, 1] training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054 test data: 110 users, 99 items, 2974 ratings, sparsity 72.69054 Load model from model.txt Set num_factors to 5 MatrixFactorization num_factors=5 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 0.40042 MAE 0.37452 NMAE 0.37452 testing_time 00:00:00.0036880 predicting_time 00:00:00.0103910 memory 0 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s] ===== MAIN: predict/evaluate on test data ===== === START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in === END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [1s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out loading_time 0.11 ratings range: [0, 1] training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054 test data: 105 users, 85 items, 1274 ratings, sparsity 85.72549 Load model from model.txt Set num_factors to 5 MatrixFactorization num_factors=5 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 0.39251 MAE 0.37112 NMAE 0.37112 testing_time 00:00:00.0027030 predicting_time 00:00:00.0661980 memory 0 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [2s] real 0m10.523s user 0m8.009s sys 0m2.224s
Run specification 
Results
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